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academic-figureslisted

Publication-ready scientific figures from one command — 22 chart types (bar, grouped bar, scatter, heatmap, forest plot, KM survival curve (Kaplan-Meier), ROC, violin, box, composite panels, PRISMA 2020 flow, funnel, Bland-Altman, PCA, venn 2-4 sets, clustered heatmap, dual-axis, Cox multi-variable regression forest), 9 themes incl. colorblind-safe Okabe-Ito and NEJM/Lancet/Science journal palettes, 9 journal submission presets, YAML figure pipeline (a whole paper in one command), multi-format export (TIFF/PNG/PDF in one run), Python API, --wizard chart picker, render watchdog with auto-degrade retry, reviewer-style --annotate arrows, PDF text-overlap + font-size gates, 600dpi output. 100% local — data never leaves your machine.
docsor1212/academic-figures · ★ 1 · Data & Documents · score 67
Install: claude install-skill docsor1212/academic-figures
<!-- ═══════════ Metadata archive (2026-09-13 frontmatter normalization) ═══════════ ZCode skill auto-discovery only reads the frontmatter whitelist keys: name / description / when_to_use / license / metadata and a description over 1024 characters is silently dropped (root cause of the v2.x auto-discovery failure: v2.4 had 1035 chars, v2.5 initial 1253). The following keys were moved out of frontmatter (info preserved): version: 3.6.0 date: 2026-09-17 author: docsor1212 metadata: {clawdbot: {emoji: "📊", category: visualization}} requires: {python: ">=3.8", pip: [matplotlib, numpy, pymupdf, scipy, openpyxl]} Runtime deps: requirements.txt and scripts/setup_env.py; history: Version History below. ═════════════════════════════════════════════════════════════════ --> # Academic Figures — Publication-Quality Chart Generator Generate figures from JSON/CSV/Excel data. Local execution, no data leaves the machine. > ⚡ **Top-3 boundaries**: add `--verify` for submission PDFs (PDF only); `--journal` > locks the figure width (`--width` is ignored); cluster_heatmap >3000 rows auto-downsamples > to 2000. **One command, verified output:** ```bash python3 scripts/gen_figure.py -t bar -d data.json -o fig.pdf --theme okabe-ito --verify # exit codes: see "Data Validation & Exit Codes" below; --verify overlap = exit 2 (fix, don't ship) ``` ## Quick Start ```bash # 0️⃣ First run: one-command environment setup (deps/CJK font/font cache/self-check) python3 scripts/setup_env.py #